I am trying to learn a time series (Mackey-Glass) using a neural net. In order to see if there has been success in the learning process, I am looking at the correlations between the predicted and real values.
The following table shows these correlations:
The correlation between the predicted value and the actual real value
real_lag_0 is 0.986. Now comparing the predicted value with the real value shifted backwards by one
real_lag_1 yields 0.993.
It seems like the highest correlation occurs at lag 1. Compare this source
If the lag is 1, then the neural net is worthless?
How could I improve the model to obtain the highest correlation for actual values?